patrickvonplaten commited on
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f985b1c
1 Parent(s): e990e13

merge conflict

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__pycache__/compel.cpython-310.pyc ADDED
Binary file (552 Bytes). View file
 
compel_run.py ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ #!/usr/bin/env python3
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+ from diffusers import DiffusionPipeline
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+ from huggingface_hub import HfApi
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+ import os
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+ from pathlib import Path
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+ from compel import Compel
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+ import torch
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+
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+ api = HfApi()
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+
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+ pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", variant="fp16", use_safetensors=True, torch_dtype=torch.float16).to("cuda")
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+ compel = Compel(tokenizer=[pipeline.tokenizer, pipeline.tokenizer_2] , text_encoder=[pipeline.text_encoder, pipeline.text_encoder_2], use_penultimate_clip_layer=True, use_penultimate_layer_norm=False, requires_pooled=[False, True])
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+
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+ # upweight "ball"
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+ prompt = "a cat playing with a ball-- in the forest"
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+ conditioning, pooled = compel(prompt)
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+
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+ # generate image
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+ image = pipeline(prompt_embeds=conditioning, pooled_prompt_embeds=pooled, num_inference_steps=30).images[0]
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+
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+ file_name = f"ball_minus_minus"
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+ path = os.path.join(Path.home(), "images", f"{file_name}.png")
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+ image.save(path)
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+
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+ api.upload_file(
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+ path_or_fileobj=path,
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+ path_in_repo=path.split("/")[-1],
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+ repo_id="patrickvonplaten/images",
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+ repo_type="dataset",
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+ )
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+ print(f"https://huggingface.co/datasets/patrickvonplaten/images/blob/main/{file_name}.png")
image.jpg ADDED
run_local_xl.py CHANGED
@@ -17,26 +17,35 @@ api = HfApi()
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  start_time = time.time()
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  use_refiner = bool(int(sys.argv[1]))
 
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- # pipe_1 = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
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- pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/nichijoufan777/stable-diffusion-xl-base-0.9/blob/main/sd_xl_base_0.9.safetensors", torch_dtype=torch.float16, use_safetensors=True)
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- pipe.to("cuda")
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- # pipe.enable_model_cpu_offload()
 
 
 
 
 
 
 
 
 
 
 
 
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- if use_refiner:
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- refiner = StableDiffusionXLImg2ImgPipeline.from_single_file("https://huggingface.co/nichijoufan777/stable-diffusion-xl-refiner-0.9/blob/main/sd_xl_refiner_0.9.safetensors", torch_dtype=torch.float16)
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- refiner.to("cuda")
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  prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
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  seed_everything(0)
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- image = pipe(prompt=prompt, output_type="latent" if use_refiner else "pil").images[0]
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  # image = pipe(prompt=prompt, output_type="latent" if use_refiner else "pil").images[0]
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  if use_refiner:
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- image = refiner(prompt=prompt, image=image[None, :]).images[0]
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  # pipe.unet.to(memory_format=torch.channels_last)
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- # pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
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  # pipe(prompt=prompt, num_inference_steps=2).images[0]
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  # image = pipe(prompt=prompt, num_images_per_prompt=1, num_inference_steps=40, output_type="latent").images
 
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  start_time = time.time()
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  use_refiner = bool(int(sys.argv[1]))
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+ use_diffusers = True
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+ if use_diffusers:
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+ start_time = time.time()
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+ pipe = StableDiffusionXLPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", torch_dtype=torch.float16, variant="fp16", use_safetensors=True, local_files_only=True)
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+ pipe.to("cuda")
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+
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+ if use_refiner:
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+ refiner = StableDiffusionXLImg2ImgPipeline.from_pretrained("stabilityai/stable-diffusion-xl-refiner-0.9", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
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+ refiner.to("cuda")
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+ # refiner.enable_sequential_cpu_offload()
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+ else:
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+ pipe = StableDiffusionXLPipeline.from_single_file("https://huggingface.co/stabilityai/stable-diffusion-xl-base-0.9/blob/main/sd_xl_base_0.9.safetensors", torch_dtype=torch.float16, use_safetensors=True)
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+ pipe.to("cuda")
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+
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+ if use_refiner:
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+ refiner = StableDiffusionXLImg2ImgPipeline.from_single_file("https://huggingface.co/stabilityai/stable-diffusion-xl-refiner-0.9/blob/main/sd_xl_refiner_0.9.safetensors", torch_dtype=torch.float16, use_safetensors=True)
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+ refiner.to("cuda")
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  prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
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  seed_everything(0)
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+ image = pipe(prompt=prompt, num_inference_steps=2, output_type="latent" if use_refiner else "pil").images[0]
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  # image = pipe(prompt=prompt, output_type="latent" if use_refiner else "pil").images[0]
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  if use_refiner:
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+ image = refiner(prompt=prompt, num_inference_steps=5, image=image[None, :]).images[0]
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  # pipe.unet.to(memory_format=torch.channels_last)
 
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  # pipe(prompt=prompt, num_inference_steps=2).images[0]
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  # image = pipe(prompt=prompt, num_images_per_prompt=1, num_inference_steps=40, output_type="latent").images